1. Molecular medicine - 2

2. Key concepts Positional cloning in identifying disease alleles
(an example – cystic fibrosis)
Majority of human diseases have polygenic or multi-factorial risk factors.
Challenges and approaches in the post genomic era

3. Example of identifying a disease allele by positional cloning Cystic fibrosis

4. Pathology
‘Woe to that child which when kissed on the forehead tastes salty. He is bewitched and soon must die’

5. cystic fibrosis caused by mutations in the CF gene
Example of identifying a disease allele by positional cloning Cystic fibrosis
Severe autosomal recessive condition among Caucasians.
5% of Caucasians are asymptomatic carriers.
Frequency of 1 / 2,500 (~ 30,000)
CF disease locus identified on chromosome 7q 31.2
(Kerem 1989; Riordan 1989; Rommens 1989).
cystic fibrosis caused by mutations in the CF gene

6. CF gene encodes a cystic fibrosis transmembrane conductance regulator (CFTR Cl- channel)
CFTR is a Cl- channel (defects result in either a decrease in its Cl- transport capacity or its level of cell surface expression)
The genetic analysis showed that this gene, which is responsible for this disorder, contains 24 exons spreading over 250 kb of chromosome 7 (7q31) and encodes an mRNA of 6.5 kb.

7. CFTR function
epithelial Cl- transport Cl- transport rate determined by activation of CFTR which in turn depends on its state of phosphorylation.
Acts as a regulator of other channels & transporters e.g CFTR mediates cAMP regulation of amiloride sensitive epithelial Na+ channels (EnaCs)

8. Mutations in CFTR 70% of CF patients show a specific deletion F508
deletion in exon 10 (F): NBD-1 domain
CFTR misfolding in the ER and
targeted for proteosome degradation

9. Mutations in CFTR

10. Mapping of CF allele
1985 gene for CF linked to enzyme paraoxanase (PON)
PON mapped to chromosome 7 and CF mapped to 7q31-32 (random DNA marker D7S15)
2 flanking markers established (~2x106bp apart)
proximal MET oncogene and distal D7S8
extensive mapping and characterisation around the candidate region by chromosome walking, chromosome jumping and microdissection (~300kbp cloned)

11. CFTR candidate region

12. Mapping of CFTR
2 new markers identified – KM19 and XV2c – which showed strong linkage disequilibrium
5’ end of gene located
Bovine equivalent of candidate gene isolated from genomic library
7 cDNA libraries screened with human clone. 1 cDNA clone identified. Northern blots show 6.5 kb mRNA
Rest of the gene obtained by screening and PCR
1989 CFTR gene eventually isolated by mutation screening

13. linkage disequilibrium
Alleles at 2 or more loci that show a non-random association are said to be in linkage disequilibrium.
Linkage disequilibrium (LD) is a term used in the study of population genetics for the non-random association of alleles at two or more loci, not necessarily on the same chromosome. It is not the same as linkage, which describes the association of two or more loci on a chromosome with limited recombination between them. LD describes a situation in which some combinations of alleles or genetic markers occur more or less frequently in a population than would be expected from a random formation of haplotypes from alleles based on their frequencies.
Linkage disequilibrium is caused by fitness interactions between genes or by such non-adaptive processes as population structure, inbreeding, and stochastic effects. In population genetics, linkage disequilibrium is said to characterize the haplotype distribution at two or more loci.
Conclusive evidence
defective cAMP-dependent chloride conductance in CFTR-/- cells was restored when CFTR cDNA was transfected and expressed in those cells.

14. Letter to Dr. Collins. Courtesy of the National Human Genome Research Institute

15. “For any given trait there will be few (if any) large effects, a handful of modest effects, and a substantial number of genes generating small or very small increases in disease risk.”
Nature 447, 661–678 (2007)
If that is the case, the existing paradigm
of drug discovery and development
requires radical rethinking, as does the
concept of personalized medicine based
solely on genetics. Exit the silver bullet
and enter the carronade (the carronade
was a short-barrel, large-diameter cannon
that could be lo

16. Challenges Some of the complexities of human disease traits
Phenotypic heterogeneity
Phenocopies
Variable expressivity
Incomplete penetrance
Polygenic traits

17. Same genotypic mutation causes variable phenotypes
Phenotypic heterogeneity
Same genotypic mutation causes variable phenotypes
e.g. a/b-thalassemias
Caused by mutations in either the a or b-globin genes.
Similar genotype can lead to unaffected or severe phenotypes

18. Many mechanisms contribute to the phenotypic heterogeneity of thalassaemias

19. Phenocopy
Disease phenotype is not caused by any known inherited predisposing mutation
e.g. BRCA1 mutations
33% of women who do not carry BRCA1 mutation develop breast cancer by age 55

20. Variable expressivity
Expression of a mutant trait differs in individuals

21. Incomplete penetrance
– when a mutant genotype does not always cause a mutant phenotype
Positional cloning identified BRCA1 as one gene causing breast cancer.
Only 66% of women who carry BRCA1 mutation develop breast cancer by age 55
Incomplete penetrance hampers linkage mapping and positional cloning

22. Polygenic traits
Two or more genes interact in the expression of phenotype e.g. cancer
QTLs, or quantitative trait loci
Penetrance / expressivity may vary with number of mutant loci
Some mutant genes may have large effect
Mutations at some loci may be recessive while others may be dominant or codominant

23. Alzheimer’s disease
Affects 5% of people >65 years and 20% of people over 80
has familial (early-onset) or sporadic (late-onset) forms, although pathologically both are similar
etiology of sporadic forms unknown
familial AD – mutations in APP, presenilin-1 and 2
Sporadic AD – strong association with APOe4, Apolipoprotein e4, which affects age of onset rather than susceptibility
3 major alleles (APO E2, E3, and E4)
Sudden cardiac death (SCD)

24. Apart from SNPs, structural variants such as CNVs may explain some of these complexities
Changes in copy number may directly affect risk factor
Rearrangements / fusion may alter expression
CNVs could increase risk of secondary pathogenic rearrangements
CNVs could indirectly affect environmental interaction leading to different phenotypes

25. What approaches should be used in the post-genomic era?

26. Mapping complex loci PAF – population attributable factor:
Fraction of the disease that would be eliminated if the risk factor were removed
High PAF for single gene conditions (>50% for CF)
Low PAF for complex disease (< 5% for Alzheimer’s)

27. Identifying genes involved in complex diseases
Perform family, twin or adoption studies
- check for genetic component
Segregation analysis
- estimate type and frequency of susceptibility alleles
Linkage analysis
- map susceptibility loci
Population association
- identify candidate region
Identify DNA sequence variants conferring susceptibility

28. Linkage versus Association
Linkage analyses search for regions of the genome with a higher-than-expected number of shared alleles among affected individuals within a family.
Used to identify rare high-risk disease alleles
<500 markers needed for initial genome scan
Association studies compare the allele frequency of a polymorphic marker, or a set of markers, in unrelated patients (cases) and healthy controls to identify markers that differ significantly between the two groups.
Used to identify common modest-risk disease variants
Higher density of markers needed
e.g. HapMap uses association data

29. Haplotype Map (HapMap)
Haplotype: specific combination of 2 or more DNA marker alleles situated close together on the same chromosome (cis markers). E.g. SNPs
HapMap - catalog of common genetic variants in populations
International HapMap Project - identify common haplotypes in four populations with African, Asian, and European ancestry
provide information to link genetic variants to the risk of disease
Figure 2: The construction of the HapMap occurs in three steps. (a) Single nucleotide polymorphisms(SNPs) are identified in DNA samples from multiple indivduals. (b)Adjacent SNPs that are inherited together are compiled into "haplotypes." (c)"Tag" SNPs within haplotypes are identified that uniquely identify those haplotypes. By genotyping the three tag SNPs shown in this figure, researchers can identify which of the four haplotypes shown here are present in each individual

30. Optional Reading on Molecular medicine
HMG3 by T Strachan & AP Read : Chapter 14
AND/OR
Genetics by Hartwell (2e) chapter 11
References on Cystic fibrosis:
Science (1989) vol 245 pg 1059 by JM Rommens et al (CF mapping)
J. Biol Chem (2000) vol 275 No 6 pp 3729 by MH Akabas (CFTR)
Optional Reading on Molecular medicine
Nature (May2004) Vol 429 Insight series
human genomics and medicine pp439 (editorial)
Nature Vol 437|27 pp October 2005 (HapMap Project)
Nature (Oct 2007) VOLUME 82 NUMBER 4 pp (CNVs)